AI SECURITY & GUARDRAILS
Build Trust Into Every Layer of AI
Every package, model and agent is secured and governed before it ships, and stays governed once it’s running.
Security Risks Scale Faster Than Teams Can Keep Up
Every new model, package and integration expands your attack surface, and most security teams can’t see what’s actually running in production. Agentic AI makes it worse when agents pick their own dependencies and tools.
60% of AI Breaches
will come from compromised models and datasets by 2029.
350K+ Safety & Security Issues
found across 2M+ publicly available AI models.
800K+ Python Packages
in the wild, available to developers with no security guardrails.
143K+ Vulnerabilities
found over 2 months across 25K MCP servers, affecting 73% of them.
The Cost of an Unvetted AI
Every unvetted package, model and agent creates exposure, whether you see it or not. Incident response, breach disclosure and compliance findings all cost more than the secure foundation and validation that would have caught it first.
Trust That Extends From Python Packages to AI Agents
For more than a decade, Anaconda has helped enterprises build on trusted Python and open source. Today, that trust extends across packages, models, agents and MCPs across the full AI-native development lifecycle from experimentation to production.
- 50M+ users and 95% of the Fortune 500 run on Anaconda.
- SOC 2, HIPAA, GDPR, and CCPA compliance support built into the platform’s access and audit layer.
New to Anaconda
Trust Can't Be Added After an AI Agent Ships
AI development is getting more agentic. Enkrypt AI brings security validation and guardrails right into your workflow running inside your own environment and tools of your choice.
- Red-teamed models from Anthropic, OpenAI, Gemini & more
- Recognized as a Gartner Cool Vendor, 2025
Move AI to Production With Continuous Assurance
Every package, model and agent follows a governed path through pre-deployment validation, runtime protection and continuous compliance. Anaconda’s trusted open-source foundation combines with Enkrypt AI’s agent security capabilities to extend trust from development through production.
Validate Before It Ships
Automated adversarial security testing of AI models and agents before they ship and continuous evaluation after deployment.
- Pre- and post-deployment security red-teaming across 300+ attack categories.
- Continuous package and model scanning: security vulnerabilities, license issues and malicious code caught before anything reaches production.
Constrain What It's Allowed to Do
Runtime guardrails constrain agent behavior in real time.
- MCP governance keeps agents inside approved scope, enforced inside your own environment, never an external provider.
- Role-based access and SSO across every package, model and environment you use.
- Real-time monitoring catches drift and anomalies as they happen.
Prove It Stayed in Policy
Continuous evidence collection for AI regulatory frameworks, not a periodic audit.
- Complete audit trail and lineage: every package, environment, model and agent action logged, down to the exact configuration.
- Automated compliance tracking for the EU AI Act, NIST AI RMF, and SOC 2.
- Full AI-BOM and SBOM generated automatically.
Continuously Govern AI Where It Runs
Security validation, guardrails and policy enforcement run inside your environment across clouds, frameworks and models. Compliance becomes an everyday operating control, not a once-a-year audit exercise.
From Manual Audit to Enforced Control
Without AI Security & Guardrails
|
With AI Security & Guardrails
No visibility into what packages are actually running
→
Continuous vulnerability scanning and usage observability
Access controls are ad hoc or missing
→
Governed access policies and enterprise SSO/RBAC
Discover unsafe agent behavior after an incident
→
Red-team models and agents before they ship
Hope agents stay in scope
→
Runtime guardrails constrain behavior in real time
Manually track what tools an agent can reach
→
MCP governance bounds and audits every connection
Compliance is a once-a-year scramble
→
Compliance evidence collected automatically, continuously
Trust routed through an external provider's promises
→
Validation runs inside your own environment
Security is a gate at the end of the workflow
→
Security is built into every step
Keep Every Team Moving Without Losing Control
Security Leaders
Enforce security and compliance without becoming the bottleneck. Automated evidence maps EU AI Act and NIST AI RMF requirements to continuous controls.
AI & Platform Teams
Enable innovation without another stack to manage. Give teams consistency, keep developer choice.
Builders
Ship agents without waiting for manual security reviews. Guardrails operate automatically in the environment where you already build and run.
Stay Governed as AI And Regulation Evolve
The attack surface keeps expanding while the security and compliance bar continues to rise. New models, connections and regulatory requirements should strengthen existing controls, not create another governance process.
- Map new frameworks to existing controls without rebuilding your audit program.
- Give every new model and MCP server the same governed path as those already in production.
AI Security & Guardrails Is Where Trust Gets Proven
AI Security & Guardrails provides continuous assurance across the Anaconda Platform: build in AI Workspaces, validate and protect before and after deployment, then scale with AI Orchestration.
BUILD
AI Workspaces
Packages, models, and agentic development environments to build with.
SCALE
AI Orchestration
Get more AI ideas out of experimentation and into production, faster.
How Will You Keep Your Next AI Build Trusted?
How it works:
Complete the form, and we’ll reach out within 1 business day to discuss your requirements. Then, we’ll build a demo that addresses your real challenges.